Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions

The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale

A benefit dependency network for shadow information technology adoption, based on practitioners’ viewpoints

Shadow information technology (SIT) revolves around systems that are hidden but are still managed by the same business entities. It consists of the use of devices, software, systems and applications without the information technology (IT) department’s approval. Employees use IT without the knowledge of the IT department, and it creates a gap in communications, as the IT department loses the knowledge of the reality within the company. However, there are benefits involved. In order to take advantage of these benefits, changes have to be implemented in the way that business activities are handled. The benefits should be a direct result of the changes, of the difference between the ongoing and the suggested way that activities should be undertaken, and the levels of efficiency and effectiveness to which people deliver their daily tasks. The objective of this study was to propose a benefit dependency network (BDN) for SIT, and, through its concepts, to synthetize our findings and specify the connections between SIT practices and their benefits. This research was conducted a systematic literature review (SLR) and used a design science research methodology, adopting semi-structured interviews with fourteen interactions to propose a BDN for SIT. We proposed a model with five dimensions related to a BDN for SIT. By understanding the BDN and the benefits of SIT, it is easier to have a better notion of the implications and the factors involved in order to assist the decision-making process. Whether an organization wants to reach innovation, increase revenue or retain clients, the BDN helps with analysis and selection, and is something that organizations should take seriously, as it is essential to have knowledge about what the benefits are and how they can be reached. To the best of the authors’ knowledge, this research included and replaced several processes in the BDN for SIT, in a topic that is still underexplored.info:eu-repo/semantics/publishedVersio

Extensibility of Enterprise Modelling Languages

Die Arbeit adressiert insgesamt drei Forschungsschwerpunkte. Der erste Schwerpunkt setzt sich mit zu entwickelnden BPMN-Erweiterungen auseinander und stellt deren methodische Implikationen im Rahmen der bestehenden Sprachstandards dar. Dies umfasst zum einen ganz konkrete Spracherweiterungen wie z. B. BPMN4CP, eine BPMN-Erweiterung zur multi-perspektivischen Modellierung von klinischen Behandlungspfaden. Zum anderen betrifft dieser Teil auch modellierungsmethodische Konsequenzen, um parallel sowohl die zugrunde liegende Sprache (d. h. das BPMN-Metamodell) als auch die Methode zur Erweiterungsentwicklung zu verbessern und somit den festgestellten Unzulänglichkeiten zu begegnen. Der zweite Schwerpunkt adressiert die Untersuchung von sprachunabhängigen Fragen der Erweiterbarkeit, welche sich entweder während der Bearbeitung des ersten Teils ergeben haben oder aus dessen Ergebnissen induktiv geschlossen wurden. Der Forschungsschwerpunkt fokussiert dabei insbesondere eine Konsolidierung bestehender Terminologien, die Beschreibung generisch anwendbarer Erweiterungsmechanismen sowie die nutzerorientierte Analyse eines potentiellen Erweiterungsbedarfs. Dieser Teil bereitet somit die Entwicklung einer generischen Erweiterungsmethode grundlegend vor. Hierzu zählt auch die fundamentale Auseinandersetzung mit Unternehmensmodellierungssprachen generell, da nur eine ganzheitliche, widerspruchsfreie und integrierte Sprachdefinition Erweiterungen überhaupt ermöglichen und gelingen lassen kann. Dies betrifft beispielsweise die Spezifikation der intendierten Semantik einer Sprache

AIM Triad: A Prioritization Strategy for Public Institutions to Improve Information Security Maturity

In today’s world, private and government organizations are legally obligated to prioritize their information security. They need to provide proof that they are continually improving their cybersecurity compliance. One approach that can help organizations achieve this goal is implementing information security maturity models. These models provide a structured framework for measuring performance and implementing best practices. However, choosing a suitable model can be challenging, requiring cultural, process, and work practice changes. Implementing multiple models can be overwhelming, if possible. This article proposes a prioritization strategy for public institutions that want to improve their information security maturity. We thoroughly analyzed various sources through systematic mapping to identify critical similarities in information security maturity models. Our research led us to create the AIM (Awareness, Infrastructure, and Management) Triad. This triad is a practical guide for organizations to achieve maturity in information security practices.This work received partial support from Proyecto DIUFRO DI21-0079 and Proyecto DIUFRO DI22-0043, Universidad de La Frontera, Temuco. Chile

IT Leadership in Transition - The Impact of Digitalization on Finnish Organizations

Digitalization is transforming business models across industries. As information technology (IT) is becoming embedded in products and services, IT leadership has an increasingly dualistic role in supporting the organization and also serving its customers' changing needs. The ACIO research program studied how Finnish industry and public sector organizations utilize information technology in developing and managing critical business capabilities. The focus was on understanding and analyzing contemporary approaches to IT leadership. This research report summarizes some of the key research findings, providing scholars and practitioners with insights into and understanding of digitalization and changes in IT leadership in Finnish informationintensive organizations

iPatient in medical information systems and future of internet of health

The results of Study "iHealthCare Optimization", provided by Dell EMC External Research and Academic Alliances, are presented. Big Data analytics of Medical information system qMS records was implemented using cluster analysis in Python. Software for cluster analysis was created by Andrey Mazelis (Vladivostok State University of Economics and Service). There are two directions of cluster analysis: Series treatment (number of investigation procedures for each patient) and Series time (waiting time for investigation procedures for each patient). Two models of patients management (Model A and Model B) were found, that can be used for better planning of care management. Models approach provides the new capability to implement Health Care Standard in mode aaS, using feedback after Big Data analytics. Around 80-90% of patients with Essential hypertension can get treatment in Day Hospital without hospitalization

Systematic Literature Review—Effects of PSS on Sustainability Based on Use Case Assessments

Product-service systems (PSS) are often presented as an inherently sustainable business model. The argumentation is often based on theoretical considerations, which cite circular economy (CE) characteristics in PSS business models as an explanation. In this paper we examined to what extent positive and negative sustainability effects of PSS could actually be observed, based on use cases. For this purpose, we conducted a systematic literature review and analyzed the statements on sustainability effects based on the triple bottom line approach. We find that positive sustainability effects, especially on the environmental sustainability of PSS, are described disproportionately often, which may be indicating a possible publication bias. In addition, the methods used to derive statements on sustainability effects are very heterogeneous and often unsystematic, making it difficult to compare the described effects. Furthermore, we were able to identify drivers that are particularly often considered in literature to be responsible for sustainability effects. As a result, we were able to derive direct implications for future research in the field of sustainability assessment of PSS.TU Berlin, Open-Access-Mittel – 202

Place and city: merging our affective and social spatial dimension in the (smart) platial city

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsWe are living in (smart) cities that hold social-oriented promises but currently, most of these cities disregard the humans. Although some alternatives are appearing such as smart citizen-centric approaches, there is a lack of how promoting truly appealing perspectives toward a common good or better social synergies. Thereby, smart cities, with their associated Information and Communication Technology tools, are offering new possibilities, but, unfortunately, citizens are not fully exploiting the opportunities to empower themselves because, among other reasons, they are not aware of their common spatialities. Currently, we are not able to operationalize the spatial humanurban interactions regarding citizens’ cognitions, feelings and behaviors towards city places (i.e., sense of place) and meaningful geographic human relationships (i.e., social capital). Both concepts are significant as resources for an alternative landscape based on human perception and organization of social interactions fostered through the geographic place(s). In this research, we highlight the need to understand and operationalize social concepts spatial dimension for a better understanding of a smart citizen-centric approach which is mainly dependent on our capability to understand platial urban dynamics. We conceptualized a (spatial) conceptual framework for sense of place and social capital at the individual level to study their spatial relationship in the urban context. We developed a web map-based survey based on the literature to spatialize, characterize and measure sense of place, social capital and civic engagement. Using the spatial data collected, we validated our framework and demonstrated the importance to encompass the spatial dimension of social concepts (i.e., sense of place and social capital) as pivotal aspect (1) to understand the platial urban dynamics; (2) to provide useful social-spatial data to city processes (e.g. civic engagement); and (3) to reveal the potential to include them in social theory and structural equation models. Furthermore, we highlighted the crucial role of Geographic Information Science (GISc) techniques to gather the spatial dimension of those social concepts. Although in this research we focus on the spatial relationship between sense of place and social capital on civic engagement, the possibilities to relate our framework and methodology to other city based-notions can bring to light new platial urban dynamics. This research wants to open up the agenda for further research into exploratory place-based geography studies and, simultaneously, sets up a common social ground to build other socially-oriented conceptualizations or applications on top of it

A Conceptual Framework to Support Digital Transformation in Manufacturing Using an Integrated Business Process Management Approach

Digital transformation is no longer a future trend, as it has become a necessity for businesses to grow and remain competitive in the market. The fourth industrial revolution, called Industry 4.0, is at the heart of this transformation, and is supporting organizations in achieving benefits that were unthinkable a few years ago. The impact of Industry 4.0 enabling technologies in the manufacturing sector is undeniable, and their correct use offers benefits such as improved productivity and asset performance, reduced inefficiencies, lower production and maintenance costs, while enhancing system agility and flexibility. However, organizations have found the move towards digital transformation extremely challenging for several reasons, including a lack of standardized implementation protocols, emphasis on the introduction of new technologies without assessing their role within the business, the compartmentalization of digital initiatives from the rest of the business, and the large-scale implementation of digitalization without a realistic view of return on investment. To instill confidence and reduce the anxiety surrounding Industry 4.0 implementation in the manufacturing sector, this paper presents a conceptual framework based on business process management (BPM). The framework is informed by a content-centric literature review of Industry 4.0 technologies, its design principles, and BPM method. This integrated framework incorporates the factors that are often overlooked during digital transformation and presents a structured methodology that can be employed by manufacturing organizations to facilitate their transition towards Industry 4.0

IoT and Sensor Networks in Industry and Society

The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society